Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …

H Tao, SI Abba, AM Al-Areeq, F Tangang… - … Applications of Artificial …, 2024 - Elsevier
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

[HTML][HTML] Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions

Y Chen, S Yu, S Islam, CP Lim, SM Muyeen - Energy Reports, 2022 - Elsevier
Recently, numerous forecasting models have been reported in the wind power forecasting
field, aiming for reliable integration of renewable energy into the electric grid. Decomposition …

Long lead-time daily and monthly streamflow forecasting using machine learning methods

M Cheng, F Fang, T Kinouchi, IM Navon, CC Pain - Journal of Hydrology, 2020 - Elsevier
Long lead-time streamflow forecasting is of great significance for water resources planning
and management in both the short and long terms. Despite of some studies using machine …

Streamflow and rainfall forecasting by two long short-term memory-based models

L Ni, D Wang, VP Singh, J Wu, Y Wang, Y Tao… - Journal of …, 2020 - Elsevier
Prediction of streamflow and rainfall is important for water resources planning and
management. In this study, we developed two hybrid models, based on long short-term …

Monthly runoff time series prediction by variational mode decomposition and support vector machine based on quantum-behaved particle swarm optimization

Z Feng, W Niu, Z Tang, Z Jiang, Y Xu, Y Liu… - Journal of Hydrology, 2020 - Elsevier
Accurate monthly runoff prediction plays an important role in the planning and management
of water resources. However, owing to climate changes and human activities, natural runoff …

Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting

G Zuo, J Luo, N Wang, Y Lian, X He - Journal of Hydrology, 2020 - Elsevier
Reliable and accurate streamflow forecasting is vital for water resource management. Many
streamflow prediction studies have demonstrated the excellent prediction ability of …

A robust method for non-stationary streamflow prediction based on improved EMD-SVM model

E Meng, S Huang, Q Huang, W Fang, L Wu, L Wang - Journal of hydrology, 2019 - Elsevier
Monthly streamflow prediction can offer important information for optimal management of
water resources, flood mitigation, and drought warning. The semi-humid and semi-arid Wei …

Streamflow forecasting using extreme gradient boosting model coupled with Gaussian mixture model

L Ni, D Wang, J Wu, Y Wang, Y Tao, J Zhang, J Liu - Journal of Hydrology, 2020 - Elsevier
The establishment of an accurate and reliable forecasting model is important for water
resource planning and management. In this study, we developed a hybrid model (namely …

Time series-based groundwater level forecasting using gated recurrent unit deep neural networks

H Lin, A Gharehbaghi, Q Zhang, SS Band… - Engineering …, 2022 - Taylor & Francis
In this research, the mean monthly groundwater level with a range of 3.78 m in Qoşaçay
plain, Iran, is forecast. Regarding three different layers of gated recurrent unit (GRU) …

Spatiotemporal characteristics and attribution of dry/wet conditions in the Weihe River Basin within a typical monsoon transition zone of East Asia over the recent 547 …

X Chen, Q Quan, K Zhang, J Wei - Environmental Modelling & Software, 2021 - Elsevier
Abstract The Weihe River Basin (WRB) in a monsoon transition zone of East Asia interacts
with multiple weather systems and is susceptible to floods and droughts. We developed a …